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The purpose of this paper is to examine the interplay between police legitimacy and protest policing with reference to the case of Hong Kong.

This study will review the concepts of police legitimacy and protest policing and examine the evolving policing practices in Hong Kong since 2010.

The study argues that the increasing polarisation of society could render policing protest a potential source of problem for sustaining police legitimacy.

This is a pioneering study that looks at the interplay between police legitimacy and protest policing.

Considering both online and offline service scenarios, this study aims to explore the factors affecting doctors' intention to offer consulting services in eHealth and compare the factors between the free- and paid-service doctors. The theory of reasoned action and social exchange theory are integrated to develop the research model that conceptualizes the role of extrinsic motivations, intrinsic motivations, costs, and attitudes in doctors' behavioral intentions.

Partial least square structural equation modeling (PLS-SEM) was leveraged to analyze 326 valid sample data. To provide robust results, three non-parametric multigroup analysis (MGA) methods, including the PLS-MGA, confidence set, and permutation test approaches, were applied to detect the potential heterogeneity between the free- and paid-service doctors.

The results with overall samples reveal that anticipated rewards, anticipated associations, anticipated contribution, and perceived fee are all positively related to attitude, which in turn positively influences behavioral intention, and that perceived fee positively moderates the relationship between attitude and behavioral intention. Attitude's full mediation is also confirmed. However, results vary between the two groups of doctors. The three MGA approaches return relatively convergent results, indicating that the effects of anticipated associations and perceived fee on attitude are significantly larger for the paid-service doctors, while that of anticipated rewards is found to be significantly larger for the free-service doctors.

eHealth, as a potential contactless alternative to face-to-face diagnoses, has recently attracted widespread attention, especially during the continued spread of COVID-19. Most existing studies have neglected the underlying heterogeneity between free- and paid-service doctors regarding their motivations to engage in online healthcare activities. This study advances the understanding of doctors' participation in eHealth by emphasizing their motivations derived from both online and offline service scenarios and comparing the differences between free- and paid-service doctors. Besides, horizontally comparing the results by applying diverse MGA approaches enriches empirical evidence for the selection of MGA approaches in PLS-SEM.

To succeed in a competitive tourist market and attract more foreign tourists, it is essential to have a clear understanding of what travellers are seeking and endeavour to meet those needs, as well as key influential factors in their travel decision-making process. The purpose of the study is to develop and examine tourists’ pre-trip motivational model using the push–pull theory.

A tourists’ pre-trip motivational model was developed and then tested based on a sample of 320 Chinese and non-Chinese visitors to Melbourne, Australia, to assess the suitability of the new model. Data were analysed by descriptive and inferential statistical techniques, such as principal component analysis and independent T-tests.

The analysis revealed statistically significant differences between studied samples in terms of the push and pull factors. In comparison with non-Chinese tourists, Chinese visitors to Melbourne assigned higher importance to resting and relaxing opportunities, family-oriented activities, as well as safety and a high level of service. The identified differences should be reflected in marketing and promotional activities provided to Chinese and non-Chinese travellers.

The study provides useful information for Destination Marketing Organisations in tourism cities wanting to develop specifically customised tourist products, services and promotion programs tailored to each market.

The proposed extended push–pull model represents a holistic and complex model of the travel decision-making process with the multiple linkages between motivations for travelling, preferences of destination attributes, information source usage, trip expectations, possible constraints for travelling and evaluation of destination choice criteria. Understanding all these factors, their relationship and their influence on the final destination choice is a prerequisite for effective and successful actions on attraction and retention of visitors for all tourist destinations. The developed tourists’ pre-trip motivational model may be used as a conceptual framework to guide subsequent motivational studies in tourism.

To protect information and communication technology (ICT) infrastructure and resources against poor cyber hygiene behaviours, organisations commonly require internal users to confirm they will abide by an ICT Code of Conduct. Before commencing enrolment, university students sign ICT policies, however, individuals can ignore or act contrary to these policies. This study aims to evaluate whether students can apply ICT Codes of Conduct and explores viable approaches for ensuring that students understand how to act ethically and in accordance with such codes.

The authors designed a between-subjects experiment involving 260 students’ responses to five scenario-pairs that involve breach/non-breach of a university’s ICT policy following a priming intervention to heighten awareness of ICT policy or relevant ethical principles, with a control group receiving no priming.

This study found a significant difference in students’ responses to the breach versus non-breach cases, indicating their ability to apply the ICT Code of Conduct. Qualitative comments revealed the priming materials influenced their reasoning.

The authors’ priming interventions were inadequate for improving breach recognition compared to the control group. More nuanced and targeted priming interventions are suggested for future studies.

Appropriate application of ICT Code of Conduct can be measured by collecting student/employee responses to breach/non-breach scenario pairs based on the Code and embedded with ethical principles.

Shared awareness and protection of ICT resources.

Compliance with ICT Codes of Conduct by students is under-investigated. This study shows that code-based scenarios can measure understanding and suggest that targeted priming might offer a non-resource intensive training approach.

The emergence of social media as a corporate disclosure channel has caused significant changes in the production and dissemination of corporate information. This review identifies important themes in recent research on the impact of social media on the corporate information environment and provides suggestions for further explorations of this new but fast-growing area of research. Specifically, we first review the evolution of Internet-based corporate disclosure and related regulations, and then focus on three recent streams of research: 1) companies’ use of social media; 2) information produced by non-corporate users and its impact on capital markets; and 3) the credibility of corporate information on social media platforms.

The significance of cloud services in information technology (IT) is increasing as a means of achieving enhanced productivity, efficiency and cost reduction. Through cloud-based service, the reliability and scalability of an organization’s systems can be enhanced since organizations such as local governments are able to concentrate on their main business strategies. This research seeks to identify critical factors that may have an impact on the acceptance of cloud-based services, where the organizational context is based on local governments in Australia.

To formulate a more comprehensive IT innovation adoption model for cloud technology, factors from the technology-organizational-environment framework, desires framework and diffusion of innovation model were integrated. Data was obtained from 480 IT staff working in 47 local government organizations.

The research results show that the factors which had a statistically significant and positive impact on the adoption of cloud-based services in local governments were compatibility, complexity, cost, security concerns, expected benefits and organization size. It is likely that the outcomes from this research will provide insights to any organization seeking to make investment decisions on the adoption of cloud-based services.

Limitations include generalizability of the findings since the data is restricted to local government areas in Queensland, Australia. Further, the sample mostly included individuals with managerial positions and may not completely capture the cloud adoption factors relevant for front line IT employees. Another limitation is the possible omission of factors that may be relevant but not considered due to the selected theories. Lastly, this research did not differentiate between different types of cloud adoption such as private, public, community and hybrid models that are possible in this context.

The paper provides a combination framework of cloud-based service adoption based on a literature review on cloud adoption from an IS perspective. It adapts integrated model to establish a more comprehensive innovation adoption framework for cloud technology.

Social media influencers (SMIs) play an increasingly important role in influencing youth and their shopping behaviours in digital marketing. Research has examined various but fragmented SMIs, which cause inconsistency in empirical results. This research seeks to categorise the most popular SMIs in luxury fashion and examine their distinctive effects on Gen Z consumption in China.

The authors categorise SMIs into four groups based on two dimensions, i.e. network interactivity vs social connectedness. Drawing on the social network theory, the authors develop the research model. A sample of 400 survey data is collected and analysed using the PLS-SEM technique.

The empirical results suggest that among the four popular SMIs groups, the effects of celebrities, opinion leaders and friends and peers on luxury fashion consumption of Gen Z are statistically significant while that of advertisers are insignificant; that friends and peers have the most substantial effect among the others.

The study contributes to understanding SMIs and consumer behaviour in digital emerging markets. By categorising SMIs, this study reconciles inconsistencies in the concept. This study contributes to a better understanding of SMIs and their roles in the digital marketing of luxury fashion consumption.

This paper aims to theorize and investigate the use of effective color features in artificial intelligence (AI) influencers, an emerging marketing trend in the social media context.

By analyzing 6,132 pictures posted by ten AI influencers on Instagram, this paper examines the effect of warm colors in AI influencers’ social media posts on consumer responses, and how other color features may moderate the effect of warm color. In addition, two experimental studies reveal the underlying process driving the effect of warm color.

Warmer color generated more favorable consumer responses, with brightness significantly moderating the relationship between warm color and favorable consumer responses. Moreover, the results of the experiments establish that perceived warmth and emotional trust mediate the causal effect of warm colors on consumer responses.

There is still little understanding about consumer perceptions of AI influencers and their acceptance of AI influencers’ product recommendations. As such, this research offers theoretical understanding of the color features influencing the effectiveness of recommendations by AI influencers.

Brands have started deploying AI influencers as their brand ambassadors to make product recommendations, representing a new wave of advertising on social media. The findings will thus benefit marketers in developing effective product recommendations using AI influencers.

The present research provides a novel understanding of how visual features, such as color can influence the effectiveness of AI influencers.

This study, guided by the feelings-as-information theory, aims to explore the effect of recovery experience of wellness tourism (REWT) on place attachment, alongside an examination into the mediating role of self-perceived health and the moderating role of health goal salience. The research site was traced for two years to monitor the evolution of the proposed model during the COVID-19 pandemic.

The successive independent samples data (in 2020 and 2021, respectively) were collected in Shizhu county, China. Structural equation modeling (SEM) was used with a survey of 1,472 wellness tourists (N₂₀₂₀ = 494, N₂₀₂₁ = 978) to test research hypotheses empirically. Additionally, independent sample t-test and multi-group SEM analysis were used to compare the mean difference of variables and coefficients’ difference between 2020 and 2021.

This study reveals that REWT can increase self-perceived health, resulting in a positive influence on place attachment. By tracing the research site and comparing the successive independent samples data, we found a stronger recovery experience effect of wellness tourism on place attachment alongside a weaker effect on self-perceived health in 2021. The positive relationship between self-perceived health and place attachment is significantly strengthened when health goals are salient.

This study investigated the mechanism behind the formation of place attachment in the wellness tourism context and extended understanding on the dynamic nature of the REWTand ongoing evolving person-place relationship during the COVID-19 pandemic. This study also provided practical suggestions to benefit industry practitioners by enhancing current understanding of improving experience-based management in wellness destinations.

Considerable evidence suggests that although they overlap, entrepreneurial and employee stressors have different causal antecedents and outcomes. However, limited empirical data explain how entrepreneurial traits, work and life drive entrepreneurial stressors and create entrepreneurial strain (commonly called entrepreneurial stress). Drawing on the challenge-hindrance framework (CHF), this paper hypothesises the causal effect of hindrance stressors on entrepreneurial strain. Furthermore, the study posits that entrepreneurial stressors and the resultant strain affect entrepreneurial behaviour.

The study adopts an SEM-based machine-learning approach. Cross-lagged path models using SEM are used to analyse the data and train the machine-learning algorithm for cross-validation and generalisation. The sample consists of 415 entrepreneurs from three countries: India, Oman and United Arab Emirates. The entrepreneurs completed two self-report surveys over 12 months.

The results show that hindrances to personal and professional goal achievement, demand-capability gap and contradictions between aspiration and reality, primarily due to unique resource constraints, characterise entrepreneurial stressors leading to entrepreneurial strain. The study further asserts that entrepreneurial strain is a significant predictor of entrepreneurial behaviour, significantly affecting innovativeness behaviour. Finally, the finding suggests that psychological capital moderates the adverse impact of stressors on entrepreneurial strain over time.

This study contributes to the CHF by demonstrating the value of hindrance stressors in studying entrepreneurial strain and providing new insights into entrepreneurial coping. It argues that entrepreneurs cope effectively against hindrance stressors by utilising psychological capital. Furthermore, the study provides more evidence about the causal, reversed and reciprocal relationships between stressors and entrepreneurial strain through a cross-lagged analysis. This study is one of the first to evaluate the impact of entrepreneurial strain on entrepreneurial behaviour. Using a machine-learning approach is a new possibility for using machine learning for SEM and entrepreneurial strain.